滨江流域GPS降水预报系统的研究与实现

 利用试验区建立的GPS水汽监测网获得的近乎实时的水汽数据，采用模块开发和系统集成方式，研制了流域GPS降水预报系统。介绍了系统的体系结构、主要功能、运行情况及开发的关键技术。叙述了流域降水预报的各种预报方法，并建立了基于遗传算法的降水预报神经网络模型(GA-BP网络模型)。结果表明，GPS水汽可为降水预报提高精度；GA-BP网络是一种精度较高的降水预报模型，可提高预测精度，增长有效预见期。该系统能根据流域GPS观测数据、高空数据、卫星云图，数值产品等数据，实现不同数据源的信息处理和不同时效的降水预报制作，为洪水预警预报和防洪决策服务。

Research and Implement of GPS Precipitation Forecast System for Binjiang River Catchment

Utilizing the real-time water vapor data obtained from GPS water vapor monitoring net in the trial zone and adopting the development of the module and system integration way, the GPS precipitation forecast system for river catchment has been developed. The structure, function, running, and key technology of the system are introduced respectively. Every method of precipitation forecast is simply depicted. An ANN model joined with GA for river catchment precipitation forecast has been set up. The result shows that the GPS water vapor and the model of GA-BP can enhance the forecast precision, and its effectiveness and the reliability has been proved. The system can realize the information processing of different data sources and the precipitation forecast of the result is made by the GPS observed data, supper-air data, satellite cloud atlas etc. of river catchment. It can service for prewarning prediction and prevent flood decision making.